Conventionally, various image processing methods have been proposed for removing defocus in an image captured by an optical system (see, for example, Patent Documents 1-3).
With such a conventional technology, filtering is executed for recovering an image based on a PSF (Point Spread Function) of an optical system. However, the PSF of an optical system often changes depending on an angle (direction) of entering light. Therefore, resolution of an imaging device such as a digital camera is usually degraded at a peripheral part of an image compared to the optical axis center part due to the optical system aberration and field angle dependency of an opening size. Picture quality degradation due to field angle dependency is especially notable with an optical system using an inexpensive lens.
To cope with such a change of PSF caused by an entering light angle, there is a technology for compensating an image that applies filtering to the image using filter data that is variable with a position of an object to be processed in the image (see, for example, Patent Document 4).
Picture quality degradation of a peripheral part in an image can be calculated with the transfer function of an optical system, which describes a degree of degradation changing with the distance from the optical axis center (least degraded part), which is set as the center of a captured image.
FIG. 1 is a schematic view illustrating an example of an optical system. FIG. 2 is a schematic view illustrating an example of degradation of the PSF. As illustrated in FIGS. 1-2, PSF degradation becomes greater as the distance from the optical axis center increases. Here, a degree of degradation at a peripheral part can be calculated based on lens data including a lens surface form, thickness, material, and the like in an the optical system described in a predetermined format (see, for example, Patent Document 4).
When using an image compensation technology that applies filtering to an image using filter data that is variable with a position of an object to be processed in the image, it is preferable to use filtering coefficients that are appropriate for a specific position.
Image compensation to recover from image degradation at a peripheral part of an image is practically implemented with applying filtering with a size of, for example, 5×5. Also, recovering from peripheral degradation requires filtering coefficients to be changed depending on a position.
In this case, an image is partitioned into areas to which applicable filtering coefficients (compensation coefficients) are calculated. Moreover, using filtering coefficients of a sample point (arbitrary pixel) in each area, filtering coefficients of pixels other than the sample point can be calculated with interpolation.
Incidentally, there is a technology for image compensation using interpolation, which is applied to luminance values, instead of filtering coefficients (see, for example, Patent Document 5-6).
For example, compensation values for pixels at sample points are provided beforehand, a compensation amount of a pixel in an area enclosed by the sample points is calculated from the sample points with, for example, bilinear interpolation for all pixels in the area.
FIG. 3 is a schematic view illustrating interpolation of pixel values. Solid-line frames illustrated in FIG. 3 define areas, a white circle represents a pixel value at a sample point in each area, and dashed-line frames define areas where interpolation is applied. FIG. 4 is another schematic view further illustrating interpolation of pixel values. As illustrated in FIG. 4, using pixel values at the sample points for bilinear interpolation, pixel values at interpolation points are obtained.